AI/ML Engineer

About

Be a part of our mission! As a world leader in creating comfortable, sustainable, and efficient climate solutions for buildings, homes and transportation, it's our responsibility to put the planet first. For us at Trane Technologies, and through our businesses including Trane® and Thermo King, sustainability is not just how we do business—it is our business. Do you dare to look at the world's challenges and see impactful possibilities? Do you want to contribute to making a better future? If the answer is yes, we invite you to consider joining us in boldly challenging what's possible for a sustainable world.

Work Model

Our BrainBox AI Workplace Presence model dedicates specific in‑office days each month to focus on relationships, learning and innovation.

Responsibilities

Ce que vous ferez / What you will do:

• Framework Implementation: Actively participate in the design and hands‑on implementation of scalable AI frameworks tailored for BrainBox AI’s ongoing and future projects.
• Model Deployment: Partner closely with ML engineers and researchers to bridge the gap between a trained model and a deployed service, solving the engineering “friction” that arises during productionization.
• Monitoring & Drift Detection: Build and deploy the “immune system” for our models—systems that track performance decay and proactively detect data and concept drift.
• Technical Support & Programming: Serve as a high‑level resource in AI programming, providing technical support to the broader team to ensure project milestones are met with precision.
• Cross‑Functional Initiatives: Help evolve existing methodologies and develop new techniques for initiatives that span across different engineering and research functions.
• Data Intelligence: Identify and interpret complex patterns within datasets to refine and enhance algorithm performance based on real‑world business requirements.
• Code Excellence: Write exceptionally clean, testable, and debuggable code. Champion documentation and software development best practices within the ML lifecycle.

Requirements

Ce dont vous aurez besoin pour réussir / What you will need to be successful:

• Bachelor’s or Master’s in Software Engineering, Computer Science, or equivalent.
• 5‑8+ years of experience in software engineering, with a significant focus on the deployment and maintenance of Machine Learning systems.
• Advanced proficiency in Python and Object‑Oriented Programming (OOP).
• Strong experience in AWS environments (Lambda, SageMaker, Glue Tables, SQS/SNS, API Gateway, CloudWatch) and navigating IAM roles for secure deployments.
• Expert‑level familiarity with pytest and unit testing frameworks to ensure code reliability.
• Deep knowledge of Linux environments and a natural instinct to automate repetitive tasks and workflows.
• A strong understanding of ML model deployment patterns and current LLM architectures.
• Ability to effectively communicate complex engineering concepts to colleagues with diverse technical backgrounds.
• A proactive teammate who acts as a “resource person” for others, sharing knowledge and troubleshooting model issues effectively.

Language Requirements

• French‑English bilingualism is required.
• In addition to fluency in French, successful candidates must have full professional proficiency in English to support and collaborate with English‑speaking clients, colleagues, and/or various stakeholders.

Compensation

• Annual Base Salary Range: $111,308.33 – $155,435.00
• Compensation Type: Salary
• Incentive Eligible: Yes
• Sales Commission Eligible: No

Disclaimer: Compensation is tailored to factors such as seniority, merit, geographic location, education, experience, travel requirements, and union designation. Benefits may vary by region, business alignment, union involvement, and employee status.

Benefits

Learn about our benefits designed for you to thrive at work and at home.